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China-ASEAN and Guangxi Multiple-Regions Cooperative Low-Carbon Logistics Internet of Things Service System Hidden Markov Optimization Model

机译:中国 - 东盟和广西多地区合作低碳物流互联网服务系统隐藏马尔可夫优化模型

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摘要

By analysis on the characteristic of low-carbon logistics, Internet of Things (IOT) Service System and economic zone, provides Multiple-Regions cooperative low-carbon logistics intelligent control optimization model. The low-carbon logistics IOT service system Hidden Markov optimization Model is in the IOT environment to use Hidden Markov Model algorithm to implement characteristic state transition monitoring on cross-region cooperative logistics process, based on network information aggregation, common distribution and cooperative control and other variations of IOT monitoring targets, determine prioritized state sequence by forward and backward algorithms as well as Viterbi algorithm, realize establishment of China-ASEAN and Guangxi Multiple-Regions cooperative low-carbon logistics optimization model and achieve intelligent control. Facts prove that on the premise of meeting IOT network variation state monitoring requirements, low-carbon logistics optimization model state selection identification rate could be improved.
机译:通过对低碳物流,物联网(IOT)服务体系和经济区的互联网的特性分析提供了多区域合作的低碳物流智能控制优化模型。低碳物流IOT服务系统的隐马尔可夫优化模型是在IOT环境中使用隐马尔可夫模型的算法来实现特征状态跃迁监测跨区域合作的物流过程中,基于网络信息的聚合,共同分配和协同控制等物联网作为监视目标的变化,通过向前和向后算法以及Viterbi算法,实现中国与东盟建立和广西多区域合作低碳物流优化模型和实现智能控制确定优先的状态序列。事实证明,在满足物联网网络变化状态监测要求的前提下,低碳物流优化模型状态选择识别率还有待改进。

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